{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import h5py\n",
    "import numpy as np\n",
    "import cartopy.crs as ccrs\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from utils import transform_coord\n",
    "from utils import make_grid\n",
    "from utils import mad_std\n",
    "from utils import spatial_filter\n",
    "from utils import interp2d\n",
    "from utils import tiffread\n",
    "from utils import binning\n",
    "from scipy.ndimage.filters import generic_filter"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "#plot data to view spatial coverage\n",
    "with h5py.File('/home/jovyan/shared/data-crossovers/Ascending.h5','r') as f_a:\n",
    "    lat   = f_a['lat'][:]\n",
    "    lon   = f_a['lon'][:]\n",
    "    h_elv = f_a['h_elv'][:]\n",
    "    t_yrs = f_a['t_year'][:]\n",
    "\n",
    "with h5py.File('/home/jovyan/shared/data-crossovers/Descending.h5','r') as f_b:\n",
    "    lat2   = f_b['lat'][:]\n",
    "    lon2   = f_b['lon'][:]\n",
    "    h_elv2 = f_b['h_elv'][:]\n",
    "    t_yrs2 = f_b['t_year'][:]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "beam                     Dataset {69163}\n",
      "cycle                    Dataset {69163}\n",
      "dac                      Dataset {69163}\n",
      "f_sn                     Dataset {69163}\n",
      "h_elv                    Dataset {69163}\n",
      "h_rb                     Dataset {69163}\n",
      "lat                      Dataset {69163}\n",
      "lon                      Dataset {69163}\n",
      "orbit                    Dataset {69163}\n",
      "q_flg                    Dataset {69163}\n",
      "rgt                      Dataset {69163}\n",
      "s_fg                     Dataset {69163}\n",
      "s_li                     Dataset {69163}\n",
      "snr                      Dataset {69163}\n",
      "spot                     Dataset {69163}\n",
      "t_sec                    Dataset {69163}\n",
      "t_year                   Dataset {69163}\n",
      "tide_earth               Dataset {69163}\n",
      "tide_load                Dataset {69163}\n",
      "tide_ocean               Dataset {69163}\n",
      "tide_pole                Dataset {69163}\n"
     ]
    }
   ],
   "source": [
    "!h5ls /home/jovyan/shared/data-crossovers/Descending.h5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "59354\n",
      "59354\n",
      "59354\n"
     ]
    }
   ],
   "source": [
    "print(len(lat))\n",
    "print(len(lon))\n",
    "print(len(h_elv))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/srv/conda/envs/notebook/lib/python3.7/site-packages/pyproj/crs/crs.py:280: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  projstring = _prepare_from_string(projparams)\n",
      "/srv/conda/envs/notebook/lib/python3.7/site-packages/pyproj/crs/crs.py:280: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  projstring = _prepare_from_string(projparams)\n",
      "/srv/conda/envs/notebook/lib/python3.7/site-packages/pyproj/crs/crs.py:280: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  projstring = _prepare_from_string(projparams)\n",
      "/srv/conda/envs/notebook/lib/python3.7/site-packages/pyproj/crs/crs.py:280: FutureWarning: '+init=<authority>:<code>' syntax is deprecated. '<authority>:<code>' is the preferred initialization method. When making the change, be mindful of axis order changes: https://pyproj4.github.io/pyproj/stable/gotchas.html#axis-order-changes-in-proj-6\n",
      "  projstring = _prepare_from_string(projparams)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<cartopy.mpl.feature_artist.FeatureArtist at 0x7f7077a20650>"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 648x648 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure(figsize=(9,9))\n",
    "ax = plt.axes(projection=ccrs.NorthPolarStereo()) #or UTM(7)\n",
    "lonu, latu = transform_coord('4326', '3413', lon, lat) #transform to polar stereo. To change to UTM, chnage the second argument to 32607\n",
    "lonu2, latu2 = transform_coord('4326', '3413', lon2, lat2)\n",
    "plt.scatter(lonu, latu, s=3, c=h_elv, alpha=.7, transform=ccrs.NorthPolarStereo(), cmap='terrain')#or UTM(7)\n",
    "plt.scatter(lonu2, latu2, s=3, c=h_elv2, alpha=.7, transform=ccrs.NorthPolarStereo(), cmap='terrain')\n",
    "plt.colorbar(fraction=0.0320, pad=0.02, label='Elevation (m)')\n",
    "ax.coastlines('50m')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "parameters:\n",
      "('input', ['/home/jovyan/shared/data-crossovers/Ascending.h5', '/home/jovyan/shared/data-crossovers/Descending.h5'])\n",
      "('output', ['./xoversv2.h5'])\n",
      "('radius', [300.0])\n",
      "('proj', ['3413'])\n",
      "('dxy', [1])\n",
      "('nres', [1, 1])\n",
      "('buff', [0])\n",
      "('mode', ['linear'])\n",
      "('vnames', ['orbit', 'lon', 'lat', 't_year', 'h_elv', 'dum', 'dum', 'dum'])\n",
      "('tspan', [None, None])\n",
      "('tile', False)\n",
      "('plot', True)\n",
      "('diff', False)\n",
      "crossing files: /home/jovyan/shared/data-crossovers/Ascending.h5 /home/jovyan/shared/data-crossovers/Descending.h5 ...\n",
      "tileing asc/des data...\n",
      "computing crossovers ...\n",
      "\n",
      "execution time: 0:00:01.011528\n",
      "number of crossovers found: 354\n",
      "statistics -> mean: -0.01 std.dev: 0.25 (m) (dt<30d)\n",
      "statistics -> mean: 0.077 std.dev: 6.944 (dvar/yr)\n",
      "ofile name -> ./xoversv2.h5\n",
      "Figure(1200x800)\n"
     ]
    }
   ],
   "source": [
    "!python ./xover.py /home/jovyan/shared/data-crossovers/Ascending.h5 /home/jovyan/shared/data-crossovers/Descending.h5 \\\n",
    "-o ./xoversv2.h5 -r 300 -p 3413 -d 1 -k 1 1 -m linear -v orbit lon lat t_year h_elv dum dum dum -q"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/home/jovyan/shared/data-crossovers/xoversv2.h5: unable to open file\n"
     ]
    }
   ],
   "source": [
    "!h5ls /home/jovyan/shared/data-crossovers/xoversv2.h5 #I'm not sure why this doesn't work"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 130,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "usage: xover.py [-h] [-o ofile] [-r radius] [-p epsg_num] [-d tile_size]\n",
      "                [-k na nd] [-b buffer] [-m {linear,cubic}]\n",
      "                [-v o x y t h b l t] [-t t1 t2] [-f] [-q] [-i]\n",
      "                ifile ifile\n",
      "\n",
      "Program for computing satellite/airborne crossovers.\n",
      "\n",
      "positional arguments:\n",
      "  ifile               name of two input files to cross (HDF5)\n",
      "\n",
      "optional arguments:\n",
      "  -h, --help          show this help message and exit\n",
      "  -o ofile            name of output file (HDF5)\n",
      "  -r radius           maximum interpolation distance from crossing location\n",
      "                      (m)\n",
      "  -p epsg_num         projection: EPSG number (AnIS=3031, GrIS=3413)\n",
      "  -d tile_size        tile size (km)\n",
      "  -k na nd            along-track subsampling every k:th pnt for each file\n",
      "  -b buffer           tile buffer (km)\n",
      "  -m {linear,cubic}   interpolation method, \"linear\" or \"cubic\"\n",
      "  -v o x y t h b l t  main vars: names if HDF5,\n",
      "                      orbit/lon/lat/time/height/bs/lew/tes\n",
      "  -t t1 t2            only compute crossovers for given time span\n",
      "  -f                  run in tile mode\n",
      "  -q                  plot for inspection\n",
      "  -i                  do not interpolate vars just take diff\n"
     ]
    }
   ],
   "source": [
    "!python xover.py -h"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "with h5py.File('xovers.h5','r') as f_xo:\n",
    "    lon_xo = f_xo['lon'][:]\n",
    "    lat_xo = f_xo['lat'][:]\n",
    "    dh_xo  = f_xo['dh_elv'][:]\n",
    "    dt_xo  = f_xo['dt_year'][:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x7f705d5ffdd0>"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
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\n",
      "text/plain": [
       "<Figure size 648x720 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#plot crossovers\n",
    "fig = plt.figure(figsize=(9,10))\n",
    "ax = plt.axes(projection=ccrs.NorthPolarStereo())\n",
    "plt.scatter(lon_xo[abs(dh_xo) <10], lat_xo[abs(dh_xo) <10], s=5,\\\n",
    "            c=dh_xo[abs(dh_xo) <10]/dt_xo[abs(dh_xo) <10], \\\n",
    "            alpha=.7, transform=ccrs.NorthPolarStereo(), cmap='coolwarm_r')\n",
    "plt.clim([-5.,5.])\n",
    "plt.colorbar(fraction=0.0320, pad=0.02, label='Elevation Change (m/yr)')\n",
    "#ax.coastlines('50m')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'dh')"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#plot dh vs dt\n",
    "plt.plot(dt_xo[abs(dh_xo) <10], dh_xo[abs(dh_xo) <10],'.')\n",
    "plt.xlabel('dt')\n",
    "plt.ylabel('dh')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([  1.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,   1.,\n",
       "          0.,   0.,   1.,   1.,   0.,   0.,   4.,   5.,  65., 261.,   7.,\n",
       "          4.,   3.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,\n",
       "          0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,   0.,\n",
       "          0.,   0.,   0.,   0.,   0.,   1.]),\n",
       " array([-176.36307721, -167.67412768, -158.98517815, -150.29622861,\n",
       "        -141.60727908, -132.91832954, -124.22938001, -115.54043048,\n",
       "        -106.85148094,  -98.16253141,  -89.47358187,  -80.78463234,\n",
       "         -72.09568281,  -63.40673327,  -54.71778374,  -46.02883421,\n",
       "         -37.33988467,  -28.65093514,  -19.9619856 ,  -11.27303607,\n",
       "          -2.58408654,    6.104863  ,   14.79381253,   23.48276206,\n",
       "          32.1717116 ,   40.86066113,   49.54961067,   58.2385602 ,\n",
       "          66.92750973,   75.61645927,   84.3054088 ,   92.99435833,\n",
       "         101.68330787,  110.3722574 ,  119.06120694,  127.75015647,\n",
       "         136.439106  ,  145.12805554,  153.81700507,  162.50595461,\n",
       "         171.19490414,  179.88385367,  188.57280321,  197.26175274,\n",
       "         205.95070227,  214.63965181,  223.32860134,  232.01755088,\n",
       "         240.70650041,  249.39544994,  258.08439948]),\n",
       " <a list of 50 Patch objects>)"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(dh_xo, 50)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Trend: -0.57 (m/yr)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "#filter for dh < 10 m and fit a linear trend - we might want to modify this to include just the glacier\n",
    "plt.plot(dt_xo[np.abs(dh_xo)<10],dh_xo[np.abs(dh_xo)<10],'.',markersize=2)\n",
    "c_fit = np.polyfit(dt_xo[np.abs(dh_xo)<10], dh_xo[np.abs(dh_xo)<10], 1)\n",
    "plt.plot(dt_xo[np.abs(dh_xo)<10], np.polyval(c_fit, dt_xo[np.abs(dh_xo)<10]),'r')\n",
    "plt.ylabel('dh (m)')\n",
    "plt.xlabel('dt (yrs)')\n",
    "print('Trend:',np.around(c_fit[0],2),'(m/yr)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "ename": "SyntaxError",
     "evalue": "unexpected EOF while parsing (<ipython-input-57-39b69affe6d9>, line 1)",
     "output_type": "error",
     "traceback": [
      "\u001b[0;36m  File \u001b[0;32m\"<ipython-input-57-39b69affe6d9>\"\u001b[0;36m, line \u001b[0;32m1\u001b[0m\n\u001b[0;31m    print(len(dt_xo[abs(dh_xo) <10]) #check how many points we're keeping\u001b[0m\n\u001b[0m                                                                         ^\u001b[0m\n\u001b[0;31mSyntaxError\u001b[0m\u001b[0;31m:\u001b[0m unexpected EOF while parsing\n"
     ]
    }
   ],
   "source": [
    "print(len(dt_xo[abs(dh_xo) <10]) #check how many points we're keeping"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [],
   "source": [
    "i_keep = ((np.abs(dh_xo) < 100) & (np.abs(dt_xo) < 1./12)) #keep height differences < 5m and <30 days"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "x_xo, y_xo, dt, dh = lon_xo[i_keep], lat_xo[i_keep], dt_xo[i_keep], dh_xo[i_keep]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(x_xo)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([ 0.,  0.,  0.,  4., 13.,  9.,  0.,  5., 24.,  0.,  7., 19.,  0.,\n",
       "         5., 54.,  0.,  4., 52.,  0.,  0., 55.,  0.,  5., 27.,  0., 20.,\n",
       "        27.,  0.,  0., 16.,  0.,  8.,  0.]),\n",
       " array([-17.        , -15.96969697, -14.93939394, -13.90909091,\n",
       "        -12.87878788, -11.84848485, -10.81818182,  -9.78787879,\n",
       "         -8.75757576,  -7.72727273,  -6.6969697 ,  -5.66666667,\n",
       "         -4.63636364,  -3.60606061,  -2.57575758,  -1.54545455,\n",
       "         -0.51515152,   0.51515152,   1.54545455,   2.57575758,\n",
       "          3.60606061,   4.63636364,   5.66666667,   6.6969697 ,\n",
       "          7.72727273,   8.75757576,   9.78787879,  10.81818182,\n",
       "         11.84848485,  12.87878788,  13.90909091,  14.93939394,\n",
       "         15.96969697,  17.        ]),\n",
       " <a list of 33 Patch objects>)"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "bins_list = np.linspace(-17, 17, 34)\n",
    "plt.hist(dt_xo*12, bins = bins_list) #should give one bin per month"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "4"
      ]
     },
     "execution_count": 50,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(dt_xo[abs(dt_xo*12) <1])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The code past this point is for bias analysis. Given that there are so few short-period(<30 days) crossovers, I din't see much point in doing that, unless we feel comfortable using a longer time interval as 'short-period.' Apparently we have very few in the 0-30 day range, but a lot in the 30-60 days range...."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Frequency')"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.hist(dh[np.abs(dh) < 1.5], 100,edgecolor='k')\n",
    "plt.xlabel('dh less than 30 days (m)')\n",
    "plt.ylabel('Frequency')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "print('A/D-Bias:',np.around(np.nanmedian(dh)*100,2), 'cm')\n",
    "print('Error:',np.around(mad_std(dh)*100,2), 'cm')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "#look at spatial distribution of offset\n",
    "fig = plt.figure(figsize=(9,10))\n",
    "ax = plt.axes(projection=ccrs.SouthPolarStereo())\n",
    "plt.scatter(lon_xo, lat_xo, s=5,\\\n",
    "            c=dh, \\\n",
    "            alpha=.7, transform=ccrs.PlateCarree(), cmap='coolwarm_r')\n",
    "plt.clim([-0.5, 0.5]) #modify as needed\n",
    "plt.colorbar(fraction=0.0320, pad=0.02, label='offset (m)')\n",
    "ax.coastlines('50m')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "Xs, Ys, Zs = tiffread('/home/jovyan/shared/data-crossovers/slope.tif')[0:3]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([[[  0,   0,   0, 255],\n",
       "        [  0,   0,   0, 255],\n",
       "        [  0,   0,   0, 255],\n",
       "        ...,\n",
       "        [  0,   0,   0, 255],\n",
       "        [  0,   0,   0, 255],\n",
       "        [  0,   0,   0, 255]],\n",
       "\n",
       "       [[  0,   0,   0, 255],\n",
       "        [  0,   0,   0, 255],\n",
       "        [  0,   0,   0, 255],\n",
       "        ...,\n",
       "        [  0,   0,   0, 255],\n",
       "        [  0,   0,   0, 255],\n",
       "        [  0,   0,   0, 255]],\n",
       "\n",
       "       [[  0,   0,   0, 255],\n",
       "        [  0,   0,   0, 255],\n",
       "        [  0,   0,   0, 255],\n",
       "        ...,\n",
       "        [  0,   0,   0, 255],\n",
       "        [  0,   0,   0, 255],\n",
       "        [  0,   0,   0, 255]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[  0,   0,   0, 255],\n",
       "        [  0,   0,   0, 255],\n",
       "        [  0,   0,   0, 255],\n",
       "        ...,\n",
       "        [  0,   0,   0, 255],\n",
       "        [  0,   0,   0, 255],\n",
       "        [  0,   0,   0, 255]],\n",
       "\n",
       "       [[  0,   0,   0, 255],\n",
       "        [  0,   0,   0, 255],\n",
       "        [  0,   0,   0, 255],\n",
       "        ...,\n",
       "        [  0,   0,   0, 255],\n",
       "        [  0,   0,   0, 255],\n",
       "        [  0,   0,   0, 255]],\n",
       "\n",
       "       [[  0,   0,   0, 255],\n",
       "        [  0,   0,   0, 255],\n",
       "        [  0,   0,   0, 255],\n",
       "        ...,\n",
       "        [  0,   0,   0, 255],\n",
       "        [  0,   0,   0, 255],\n",
       "        [  0,   0,   0, 255]]], dtype=uint8)"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "slope = interp2d(Xs, Ys, Zs, x_xo, y_xo, order=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "slope.min(), slope.max(), slope.mean() #might need to filter first"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "slp_b, bias_b, error_b = binning(slope, dh, xmin=0,xmax=40, dx=4, window=4)[0:3] #mess with these parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.plot(slp_b, bias_b, '-o')\n",
    "plt.ylabel('Bias (m)')\n",
    "plt.xlabel('Slope (deg)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "plt.plot(slp_b, error_b, '-o')\n",
    "plt.ylabel('Error (m)')\n",
    "plt.xlabel('Slope (deg)')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "78.24642"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.nanmax(Zs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([[546.,   0.,   0., ...,   0.,   0.,   0.],\n",
       "        [546.,   0.,   0., ...,   0.,   0.,   0.],\n",
       "        [543.,   0.,   0., ...,   0.,   0.,   3.],\n",
       "        ...,\n",
       "        [546.,   0.,   0., ...,   0.,   0.,   0.],\n",
       "        [546.,   0.,   0., ...,   0.,   0.,   0.],\n",
       "        [546.,   0.,   0., ...,   0.,   0.,   0.]]),\n",
       " array([-9999.     , -8991.275  , -7983.551  , -6975.826  , -5968.1016 ,\n",
       "        -4960.377  , -3952.652  , -2944.9275 , -1937.2029 ,  -929.4782 ,\n",
       "           78.24642], dtype=float32),\n",
       " <a list of 546 Lists of Patches objects>)"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(Zs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([9.0318e+04, 3.5024e+04, 2.6318e+04, 2.2624e+04, 1.7196e+04,\n",
       "        8.2640e+03, 2.0450e+03, 2.1300e+02, 2.3000e+01, 8.0000e+00]),\n",
       " array([7.7851611e-04, 7.8253427e+00, 1.5649907e+01, 2.3474472e+01,\n",
       "        3.1299036e+01, 3.9123600e+01, 4.6948166e+01, 5.4772728e+01,\n",
       "        6.2597294e+01, 7.0421860e+01, 7.8246422e+01], dtype=float32),\n",
       " <a list of 10 Patch objects>)"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "Zs_f = Zs[~np.isnan(Zs)]\n",
    "plt.hist(Zs_f[Zs_f > -2000])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([ 95930.,      0.,      0.,      0.,      0.,      0.,      0.,\n",
       "             0.,      0., 202033.]),\n",
       " array([-9999.     , -8991.275  , -7983.551  , -6975.826  , -5968.1016 ,\n",
       "        -4960.377  , -3952.652  , -2944.9275 , -1937.2029 ,  -929.4782 ,\n",
       "           78.24642], dtype=float32),\n",
       " <a list of 10 Patch objects>)"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.hist(Zs_f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "78.24642"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": 69,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "parameters:\n",
      "('files', ['/home/jovyan/shared/data-crossovers/Descending.h5'])\n",
      "('ofile', ['./test.h5'])\n",
      "('mode', ['g'])\n",
      "('bbox', None)\n",
      "('dxy', [5.0, 5.0])\n",
      "('radius', [2.5, 2.5])\n",
      "('resparam', [0.5])\n",
      "('nreloc', [2])\n",
      "('niter', [5])\n",
      "('minobs', [50])\n",
      "('tspan', [])\n",
      "('tref', ['fixed'])\n",
      "('dhdtlim', [15])\n",
      "('dtlim', [0.1])\n",
      "('tstep', [1.0])\n",
      "('idmission', [0])\n",
      "('residlim', [100])\n",
      "('projo', ['3031'])\n",
      "('vnames', ['lon', 'lat', 't_year', 'h_elv', 'None', 'None', 'None'])\n",
      "('expr', [None])\n",
      "('njobs', [1])\n",
      "('model', [3])\n",
      "running sequential code ...\n",
      "loading data ...\n",
      "converting lon/lat to x/y ...\n",
      "building the k-d tree ...\n",
      "predicting values ...\n",
      "saving data ...\n",
      "**********************************************************************\n",
      "Mean: 0.85634 Std: 2.80 Min: -12.77 Max: 9.37 Model: 3\n",
      "**********************************************************************\n",
      "Execution time: 0:00:40.772019\n",
      "('Surface fit results ->', './test_sf.h5')\n",
      "('Time series values -> ', './test_ts.h5')\n",
      "('Time series errors -> ', './test_es.h5')\n"
     ]
    }
   ],
   "source": [
    "!python fitsec.py /home/jovyan/shared/data-crossovers/Descending.h5 -o ./test.h5 -v lon lat t_year h_elv None None None \\\n",
    "        -m g -d 5 5 -r 2.5 2.5 -a 0.5 -q 2 -z 15 -t 2018 2021 -f fixed -s 1 -p 3 -n 1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 65,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "usage: fitsec.py [-h] [-o outfile] [-m {p,g}] [-b w e s n] [-d dx dy]\n",
      "                 [-r r_min r_max] [-a res_param] [-q n_reloc] [-i n_iter]\n",
      "                 [-z min_obs] [-t t_min t_max] [-f ref_time] [-l dhdt_lim]\n",
      "                 [-k dt_lim] [-s t_step] [-u id_mission] [-w resid_lim]\n",
      "                 [-j epsg_num] [-v x y t h s i c] [-x expr] [-n njobs]\n",
      "                 [-p {0,1,2,3}]\n",
      "                 file [file ...]\n",
      "\n",
      "Computes robust surface-height changes from satellite/airborne altimetry.\n",
      "\n",
      "positional arguments:\n",
      "  file              file(s) to process (ASCII, HDF5 or Numpy)\n",
      "\n",
      "optional arguments:\n",
      "  -h, --help        show this help message and exit\n",
      "  -o outfile        output file name, default same as input\n",
      "  -m {p,g}          prediction mode: (p)oint or (g)rid\n",
      "  -b w e s n        bounding box for geograph. region (deg or m)\n",
      "  -d dx dy          spatial resolution for grid-solution (deg or m)\n",
      "  -r r_min r_max    min and max search radius (km)\n",
      "  -a res_param      resolution param for weighting function (km)\n",
      "  -q n_reloc        number of relocations for search radius: 0 => grid\n",
      "  -i n_iter         maximum number of iterations to solve model\n",
      "  -z min_obs        minimum obs. to compute solution\n",
      "  -t t_min t_max    min and max time for solution (yr)\n",
      "  -f ref_time       time to reference the solution to: year|fixed|variable\n",
      "  -l dhdt_lim       discard estimate if |dh/dt| > dhdt_lim (m/yr)\n",
      "  -k dt_lim         discard estimates if data-span < dt_lim (yr)\n",
      "  -s t_step         time resolution of binned time series (months)\n",
      "  -u id_mission     reference id for merging (0=sin, 1=lrm)\n",
      "  -w resid_lim      discard residual if |residual| > resid_lim (m)\n",
      "  -j epsg_num       projection: EPSG number (AnIS=3031, GrIS=3413)\n",
      "  -v x y t h s i c  name of varibales in the HDF5-file\n",
      "  -x expr           expression to apply to time (e.g. 't + 2000')\n",
      "  -n njobs          for parallel processing of multiple files\n",
      "  -p {0,1,2,3}      select design matrix (order of model fit)\n"
     ]
    }
   ],
   "source": [
    "!python fitsec.py -h"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 70,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'/home/jovyan/ScienceDataGeneration/notebooks'"
      ]
     },
     "execution_count": 70,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pwd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 71,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "accel                    Dataset {34224}\n",
      "accel_err                Dataset {34224}\n",
      "amp_seas                 Dataset {34224}\n",
      "bias                     Dataset {34224}\n",
      "chi2                     Dataset {34224}\n",
      "d_min                    Dataset {34224}\n",
      "d_ri                     Dataset {34224}\n",
      "height                   Dataset {34224}\n",
      "height_err               Dataset {34224}\n",
      "lat                      Dataset {34224}\n",
      "lon                      Dataset {34224}\n",
      "model_rms                Dataset {34224}\n",
      "n_edited                 Dataset {34224}\n",
      "n_obs                    Dataset {34224}\n",
      "pha_seas                 Dataset {34224}\n",
      "slope_x                  Dataset {34224}\n",
      "slope_y                  Dataset {34224}\n",
      "t_ref                    Dataset {34224}\n",
      "t_span                   Dataset {34224}\n",
      "trend                    Dataset {34224}\n",
      "trend_err                Dataset {34224}\n"
     ]
    }
   ],
   "source": [
    "!h5ls test_sf.h5\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 75,
   "metadata": {},
   "outputs": [],
   "source": [
    "f = h5py.File('test_sf.h5', \"r\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 78,
   "metadata": {},
   "outputs": [],
   "source": [
    "dh_dt = f['trend'][:]\n",
    "lat = f['lat'][:]\n",
    "lon = f['lon'][:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 81,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<matplotlib.colorbar.Colorbar at 0x7f72b42e6510>"
      ]
     },
     "execution_count": 81,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.scatter(lat, lon, c = dh_dt)\n",
    "plt.colorbar()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 83,
   "metadata": {},
   "outputs": [],
   "source": [
    "f2 = h5py.File('test_ts.h5', 'r')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<KeysViewHDF5 ['ts']>"
      ]
     },
     "execution_count": 86,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "f2.keys()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [],
   "source": [
    "ts = f2['ts'][:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(34224, 23)"
      ]
     },
     "execution_count": 90,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ts.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 100,
   "metadata": {},
   "outputs": [],
   "source": [
    "latitude = ts[]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 102,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([59.30542494, 59.30423615, 59.30188921, 59.29971546, 59.29722687,\n",
       "       59.29360995, 59.28915824, 59.30547889, 59.30470718, 59.30291708,\n",
       "       59.29997658, 59.29791961, 59.29546225, 59.29331596, 59.29094306,\n",
       "       59.28856589, 59.286294  , 59.28397579, 59.28164618, 59.27946517,\n",
       "       59.27709748, 59.27481534, 59.27246416, 59.27025047, 59.26784133,\n",
       "       59.23942242, 59.26319267, 59.26077184, 59.28690209, 59.2585401 ,\n",
       "       59.25619587, 59.28240743, 59.27990311, 59.25391595, 59.25153102,\n",
       "       59.27775713, 59.27527622, 59.24940136, 59.24776246, 59.27310673,\n",
       "       59.27069217, 59.26847684, 59.26622302, 59.20883197, 59.2639607 ,\n",
       "       59.26135251, 59.20676068, 59.20516362, 59.2593046 , 59.25728125,\n",
       "       59.25182998, 59.25015202, 59.24731   , 59.18678373, 59.23829345,\n",
       "       59.18132791, 59.17870823, 59.23343049, 59.17716683, 59.22911858,\n",
       "       59.22444929, 59.22205114, 59.219822  , 59.21751917, 59.21541136,\n",
       "       59.21282391, 59.18424503, 59.21048695, 59.20823418, 59.20587398,\n",
       "       59.20370597, 59.2010763 , 59.19890261, 59.19679041, 59.19393219,\n",
       "       59.1896026 , 59.18718134, 59.18495406, 59.18276286, 59.1802816 ,\n",
       "       59.17788286, 59.17597603, 59.1729355 , 59.17121354, 59.16523149,\n",
       "       59.15922568, 59.15706336, 59.15473133, 59.15240435, 59.15010019,\n",
       "       59.07831662, 59.07629207, 59.07410409, 59.07163323, 59.06885134,\n",
       "       59.06711928, 59.06417696, 59.06232557, 59.05991431, 59.05763317,\n",
       "       59.05510038, 59.17607584, 59.04587545, 59.03570598, 59.08435837,\n",
       "       59.02395003, 59.02238947, 59.04863702, 59.0462198 , 59.30589473,\n",
       "       59.04455373, 59.01544414, 59.30564859, 59.03975204, 59.29434129,\n",
       "       59.16431114, 59.03238277, 59.29287703, 59.29042201, 59.1317267 ,\n",
       "       58.99822303, 59.28825856, 59.28622091, 59.1562918 , 59.12707451,\n",
       "       59.12475407, 59.02554725, 59.02337193, 58.99651234, 58.99410267,\n",
       "       59.28008827, 59.2786302 , 59.27665587, 58.98489334, 59.27448872,\n",
       "       59.27254347, 59.26978539, 59.26761804, 59.03187963, 59.03062667,\n",
       "       59.29229785, 59.29108968, 59.02830228, 59.02597894, 58.99705116,\n",
       "       59.28981776, 59.28636288, 59.02388065, 59.28552501, 59.25352651,\n",
       "       59.25099889, 58.9901362 , 59.24887068, 59.24754044, 59.01421511,\n",
       "       59.01215782, 59.24273107, 59.24186566, 59.00705242, 59.23960966,\n",
       "       59.23731816, 59.00443471, 59.00287433, 58.97626185, 58.97378115,\n",
       "       59.26371306, 59.23491356, 59.23274013, 58.97113793, 58.96895412,\n",
       "       59.25485108, 59.23035507, 59.22805587, 58.99306828, 58.99072931,\n",
       "       58.96391152, 59.25395836, 59.25356758, 59.22692717, 59.22138609,\n",
       "       58.98806929, 58.9859254 , 58.95910962, 58.9570354 , 59.22090982,\n",
       "       59.21872026, 58.98363653, 58.95476124, 58.95216319, 59.21406477,\n",
       "       59.21157809, 59.05059758, 58.97890955, 58.94983698, 59.2382934 ,\n",
       "       59.23572728, 59.20944581, 59.20800769, 58.97408183, 58.97183214,\n",
       "       58.94295394, 59.23378678, 59.23182152, 59.2020371 , 59.07045779,\n",
       "       59.06923546, 59.0428513 , 59.04034446, 58.96947039, 58.94043291,\n",
       "       58.93808137, 59.2269899 , 59.22639924, 59.20023235, 59.19765954,\n",
       "       59.09411413, 59.06713574, 59.06464575, 59.03819961, 59.03569523,\n",
       "       58.96229549, 58.93548528, 58.93346562, 59.22431997, 59.22172701,\n",
       "       59.19567622, 59.19309455, 59.06227832, 59.06000718, 58.96031139,\n",
       "       58.95786953, 58.93115544, 58.92858904, 59.21967809, 59.21854121,\n",
       "       59.1919279 , 59.05784559, 59.05507599, 59.02872093, 59.02630595,\n",
       "       58.95251215, 58.92648538, 58.9239188 , 59.21140429, 59.05297751,\n",
       "       59.05078584, 58.94819033, 58.92122447, 58.91953628, 59.21133746,\n",
       "       59.20743507, 59.04739052, 59.04636529, 58.91470334, 59.2059142 ,\n",
       "       59.20215228, 58.93865733, 58.93630799, 58.90977019, 58.90736659,\n",
       "       59.20186911, 59.16918748, 59.16742817, 59.06543823, 58.93454266,\n",
       "       58.93150576, 58.90260705, 59.19383767, 59.19164509, 59.1652692 ,\n",
       "       59.16278918, 59.0318791 , 59.00222203, 58.92945491, 58.92687067,\n",
       "       58.90039   , 58.89781297, 59.18945642, 59.18696426, 59.16058489,\n",
       "       59.15823626, 58.92455967, 58.92194512, 58.89596248, 59.18560708,\n",
       "       59.15645066, 58.91997542, 58.91747487, 58.89069238, 58.88859354,\n",
       "       58.91504958, 58.91277716, 58.88630675, 59.04195662, 59.03971157,\n",
       "       58.91032078, 58.90812798, 58.88162816, 58.87912186, 59.16712154,\n",
       "       59.03760834, 58.9058528 , 58.90326325, 58.87660225, 59.16628778,\n",
       "       59.16379573, 59.13649226, 59.13502932, 59.00335609, 58.89841996,\n",
       "       59.16151153, 59.1591597 , 59.12896142, 59.12767863, 58.893783  ,\n",
       "       58.89169968, 59.15605883, 59.12560096, 59.1231579 , 59.02316292,\n",
       "       59.02061925, 58.88917271, 58.88668295, 59.14845025, 59.14734958,\n",
       "       59.12095718, 59.11849622, 59.01630634, 58.88434497, 58.88204115,\n",
       "       59.14544987, 59.14375955, 59.11621341, 59.11394657, 58.87946419,\n",
       "       58.87719163, 59.13981891, 59.13821966, 59.11163235, 59.10902996,\n",
       "       58.87593903, 59.13556785, 59.13349725, 59.10692434, 59.10454196,\n",
       "       58.94400885, 58.94135818, 59.13126507, 59.12887467, 59.10226237,\n",
       "       59.09974379, 58.93955776, 59.1273378 , 59.1239541 , 59.09762283,\n",
       "       59.09604418, 59.12178838, 59.12093776, 59.09096559, 58.92937437,\n",
       "       58.92728647, 59.08492082, 59.0836867 , 58.95171508, 58.92493997,\n",
       "       58.92272562, 59.08299905, 58.94943102, 58.94702315, 58.92029832,\n",
       "       58.91785371, 59.10259022, 59.0747068 , 59.07374965, 58.91587438,\n",
       "       59.10151044, 59.07190585, 59.06915876, 58.9107459 , 58.90886302,\n",
       "       59.06703622, 59.06471543, 58.90365946, 59.08936791, 59.06238106,\n",
       "       59.06009729, 58.95563533, 59.05777591, 59.05704664, 58.95185594,\n",
       "       58.95009093, 58.94791492, 58.94454288, 58.94327516, 58.92684846,\n",
       "       59.0560441 , 59.05552673, 59.01371621, 59.01306137, 59.0107195 ,\n",
       "       59.03236931, 59.00746094, 59.03051215, 59.02912153, 59.00792965,\n",
       "       58.98187506, 58.9801146 , 59.00755629, 59.003176  , 58.97793947,\n",
       "       58.97557239, 59.00226575, 58.99979445, 58.97387104, 58.99775725,\n",
       "       58.99592517, 58.9654174 , 58.98941915, 58.98786378, 58.95986954,\n",
       "       58.98620197, 58.98357101, 58.95371031, 58.9518824 , 58.94957657,\n",
       "       58.96251054, 58.95765076, 58.95706016, 58.95642006, 58.95168108,\n",
       "       58.94478838, 58.94333976, 58.91338378, 58.94249188, 58.91194127,\n",
       "       58.90793756, 58.90716744, 58.90532776, 58.89386291, 58.89268429,\n",
       "       58.8901491 , 58.8881535 , 58.8855351 , 58.883371  , 58.88263143])"
      ]
     },
     "execution_count": 102,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "latitude[~np.isnan(latitude)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 103,
   "metadata": {},
   "outputs": [],
   "source": [
    "time_series = ts[:, 6:]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 104,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(34224, 17)"
      ]
     },
     "execution_count": 104,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "time_series.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 107,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x7f72b40bd350>,\n",
       " <matplotlib.lines.Line2D at 0x7f72b40d7e90>,\n",
       " <matplotlib.lines.Line2D at 0x7f72b4061090>,\n",
       " <matplotlib.lines.Line2D at 0x7f72b4061250>,\n",
       " <matplotlib.lines.Line2D at 0x7f72b4061410>,\n",
       " <matplotlib.lines.Line2D at 0x7f72b40615d0>,\n",
       " <matplotlib.lines.Line2D at 0x7f72b4061810>,\n",
       " <matplotlib.lines.Line2D at 0x7f72b40619d0>,\n",
       " <matplotlib.lines.Line2D at 0x7f72b4061b90>,\n",
       " <matplotlib.lines.Line2D at 0x7f72b4061610>,\n",
       " <matplotlib.lines.Line2D at 0x7f72b4114710>,\n",
       " <matplotlib.lines.Line2D at 0x7f72b4061fd0>,\n",
       " <matplotlib.lines.Line2D at 0x7f72b4065210>,\n",
       " <matplotlib.lines.Line2D at 0x7f72b40653d0>,\n",
       " <matplotlib.lines.Line2D at 0x7f72b4065590>,\n",
       " <matplotlib.lines.Line2D at 0x7f72b4065750>,\n",
       " <matplotlib.lines.Line2D at 0x7f72b4065910>]"
      ]
     },
     "execution_count": 107,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(time_series)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 117,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Help on function transform_coord in module utils:\n",
      "\n",
      "transform_coord(proj1, proj2, x, y)\n",
      "    Transform coordinates from proj1 to proj2\n",
      "    usgin EPSG number\n",
      "    \n",
      "    :param proj1: current projection (4326)\n",
      "    :param proj2: target projection (3031)\n",
      "    :param x: x-coord in current proj1\n",
      "    :param y: y-coord in current proj1\n",
      "    :return: x and y now in proj2\n",
      "\n"
     ]
    }
   ],
   "source": [
    "help(transform_coord)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
